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Empirical prediction of coseismic landslide dam formation

机译:同震滑坡坝形成的经验预测

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摘要

In this study we develop an empirical method to estimate the volume threshold for predicting coseismic landslide dam formation using landscape parameters obtained from digital elevation models (DEMs). We hypothesize that the potential runout and volume of landslides, together with river features, determine the likelihood of the formation of a landslide dam. To develop this method, a database was created by randomly selecting 140 damming and 200 non-damming landslides from 501 landslide dams and > 60 000 landslides induced by the M_w 7.9 2008 Wenchuan earthquake in China. We used this database to parameterize empirical runout models by stepwise multivariate regression. We find that factors controlling landslide runout are landslide initiation volume, landslide type, internal relief (H) and the H/L ratio (between H and landslide horizontal distance to river, L). In order to obtain a first volume threshold for a landslide to reach a river, the runout regression equations were converted into inverse volume equations by taking the runout to be the distance to river. A second volume threshold above which a landslide is predicted to block a river was determined by the correlation between river width and landslide volume of the known damming landslides. The larger of these two thresholds was taken as the final damming threshold. This method was applied to several landslide types over a fine geographic grid of assumed initiation points in a selected catchment. The overall prediction accuracy was 97.4% and 86.0% for non-damming and damming landslides, respectively. The model was further tested by predicting the damming landslides over the whole region, with promising results. We conclude that our method is robust and reliable for the Wenchuan event. In combination with pre-event landslide susceptibility and frequency–size assessments, it can be used to predict likely damming locations of future coseismic landslides, thereby helping to plan emergency response.
机译:在这项研究中,我们开发了一种经验方法,可以使用从数字高程模型(DEM)获得的景观参数来估算预测同震滑坡坝形成的体积阈值。我们假设滑坡的潜在跳动和数量以及河流特征决定了滑坡坝形成的可能性。为了开发这种方法,通过从中国2008年汶川7.9级地震诱发的501个滑坡坝和6万多个滑坡中随机选择140个大坝滑坡和200个非大坝滑坡来创建数据库。我们使用此数据库通过逐步多元回归参数化经验跳动模型。我们发现控制滑坡跳动的因素是滑坡起始体积,滑坡类型,内部起伏(H)和H / L比(H和滑坡到河流的水平距离L之间)。为了获得滑坡到达河流的第一体积阈值,通过将跳动作为到河流的距离,将跳动回归方程转换为反体积方程。根据河流宽度与已知的筑坝滑坡的滑坡体积之间的相关性,可以确定第二个体积阈值(高于该阈值可预测滑坡会阻塞河流)。这两个阈值中较大的一个作为最终的阻尼阈值。将该方法应用于选定流域假定起始点的精细地理网格上的几种滑坡类型。对于非填筑和填筑的滑坡,总的预测准确度分别为97.4%和86.0%。通过预测整个地区的筑坝滑坡,对该模型进行了进一步测试,结果令人鼓舞。我们得出结论,我们的方法对于汶川事件是可靠且可靠的。结合事件发生前的滑坡敏感性和频率大小评估,可以将其用于预测未来同震滑坡的可能筑坝位置,从而有助于计划应急响应。

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